Liu, Fanghui

35 publications

ICLR 2025 How Gradient Descent Balances Features: A Dynamical Analysis for Two-Layer Neural Networks Zhenyu Zhu, Fanghui Liu, Volkan Cevher

ICML 2025 LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently Yuanhe Zhang, Fanghui Liu, Yudong Chen

NeurIPS 2025 The $\varphi$ Curve: The Shape of Generalization Through the Lens of Norm-Based Capacity Control Yichen Wang, Yudong Chen, Lorenzo Rosasco, Fanghui Liu

ICLRW 2024 Character-Level Robustness Should Be Revisited Elias Abad Rocamora, Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICMLW 2024 Demonstrations in In-Context Learning for LLMs with Large Label Space Zhan Li, Fanghui Liu, Volkan Cevher, Grigorios Chrysos

ICLR 2024 Efficient Local Linearity Regularization to Overcome Catastrophic Overfitting Elias Abad Rocamora, Fanghui Liu, Grigorios Chrysos, Pablo M. Olmos, Volkan Cevher

ICLR 2024 Generalization of Scaled Deep ResNets in the Mean-Field Regime Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

ICML 2024 High-Dimensional Kernel Methods Under Covariate Shift: Data-Dependent Implicit Regularization Yihang Chen, Fanghui Liu, Taiji Suzuki, Volkan Cevher

NeurIPSW 2024 How Do Students Become Teachers: A Dynamical Analysis for Two-Layer Neural Networks Zhenyu Zhu, Fanghui Liu, Volkan Cevher

ECCV 2024 Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy Tao Li, Weisen Jiang, Fanghui Liu, Xiaolin Huang, James Kwok

JMLR 2024 Learning with Norm Constrained, Over-Parameterized, Two-Layer Neural Networks Fanghui Liu, Leello Dadi, Volkan Cevher

MLJ 2024 Random Fourier Features for Asymmetric Kernels Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang

ICML 2024 Revisiting Character-Level Adversarial Attacks for Language Models Elias Abad Rocamora, Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICLR 2024 Robust NAS Under Adversarial Training: Benchmark, Theory, and Beyond Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios Chrysos, Volkan Cevher

AAAI 2024 The Role of Over-Parameterization in Machine Learning - The Good, the Bad, the Ugly Fanghui Liu

ICML 2023 Benign Overfitting in Deep Neural Networks Under Lazy Training Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Francesco Locatello, Volkan Cevher

TMLR 2023 Federated Learning Under Covariate Shifts with Generalization Guarantees Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher

NeurIPSW 2023 Generalization Guarantees of Deep ResNets in the Mean-Field Regime Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

NeurIPS 2023 Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher

NeurIPS 2023 On the Convergence of Encoder-Only Shallow Transformers Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

ICML 2023 What Can Online Reinforcement Learning with Function Approximation Benefit from General Coverage Conditions? Fanghui Liu, Luca Viano, Volkan Cevher

NeurIPS 2022 Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: A Polynomial Net Study Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

NeurIPS 2022 Generalization Properties of NAS Under Activation and Skip Connection Search Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

NeurIPS 2022 On the Double Descent of Random Features Models Trained with SGD Fanghui Liu, Johan Suykens, Volkan Cevher

NeurIPS 2022 Robustness in Deep Learning: The Good (width), the Bad (depth), and the Ugly (initialization) Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

NeurIPS 2022 Sound and Complete Verification of Polynomial Networks Elias Abad Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

NeurIPS 2022 Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration Fanghui Liu, Luca Viano, Volkan Cevher

AISTATS 2021 Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens

AISTATS 2021 Kernel Regression in High Dimensions: Refined Analysis Beyond Double Descent Fanghui Liu, Zhenyu Liao, Johan Suykens

MLJ 2021 Analysis of Regularized Least-Squares in Reproducing Kernel Kreĭn Spaces Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A. K. Suykens

JMLR 2021 Generalization Properties of Hyper-RKHS and Its Applications Fanghui Liu, Lei Shi, Xiaolin Huang, Jie Yang, Johan A.K. Suykens

JMLR 2020 Learning Data-Adaptive Non-Parametric Kernels Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li

AAAI 2020 Random Fourier Features via Fast Surrogate Leverage Weighted Sampling Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang, Johan A. K. Suykens

AAAI 2018 Nonlinear Pairwise Layer and Its Training for Kernel Learning Fanghui Liu, Xiaolin Huang, Chen Gong, Jie Yang, Li Li

ICCVW 2015 Visual Tracking via Nonnegative Regularization Multiple Locality Coding Fanghui Liu, Tao Zhou, Jie Yang, Irene Y. H. Gu